System and method for a serialized data service

ABSTRACT

The present disclosure includes a system and method for a serialized data service. A method for a serialized data service [ 801 ] includes retrieving serialized data to a data service [ 803 ], and augmenting the serialized data with information corresponding to one or more data retention policies [ 809 ]. The augmented serialized data is stored to a data source [ 811 ]. The augmented serialized data is removed from the data source based on the augmented information [ 813].

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is related to (1) PCT Application serial number______, attorney docket number 201000505-1, entitled “System and Methodfor Service Recommendation Service,” filed on the same date as thepresent application, (2) PCT Application serial number ______, attorneydocket number 201000495-1, entitled “System and Method for CollaborativeInformation Services,” filed on the same date as the presentapplication, (3) PCT Application serial number ______, attorney docketnumber 201000503-1, entitled “System and Method for Automated DataDiscovery Service,” filed on the same date as the present application,and (4) PCT Application serial number ______, attorney docket number201000497-1, entitled “System and Method for Self-Service Configurationof Authorization,” filed on the same date as the present application,the disclosures which are incorporated herein by reference.

BACKGROUND

Information can have great value. Assembling and maintaining a databaseto store information involves real costs. The costs can include thecosts to acquire the information, the costs associated with the physicalassets used to house, secure, and make the information available, and/orthe labor costs to manage the information.

Some of the value of certain information may be derived from the factthat the information is not widely known (e.g., not shared). Forexample, a list of suppliers, their products and pricing, or a customerlist, may be valuable to a manufacturing entity, which likely would notbe inclined to share such information with its competitors. Conversely,some of the value of other information may be derived from the fact thatthe information is widely known (e.g., shared). For example, a librarycatalog is information that can be valuable to a community of users bybeing widely available, thereby saving time, effort, and perhaps moneyin trying to locate a particular item in a collection of items.

Some competitive information that principally derives value from notbeing widely known (e.g., among competitors and/or customers) may deriveadditional value were it shared with other entities in a limited manner.One such example is information related to a supply chain. A supplychain is a system of organizations, people, technology, activities,information and resources involved in moving a product or service fromsupplier to customer. A service can include a wholly electronicworkflow, in which case “fulfillment” is the completion of a specificset of possibly entirely-electronic tasks, with the appropriate temporalordering. A supply chain may be a combination of products and services.For example, services that monitor and provide local control overelectricity usage by customers may help to control the generation andsupply of electricity to customers. Relationships of participants in asupply chain may include supplier-customer, and/or competitors, amongothers. Regulators and/or consumers may also have an interest ininformation concerning a particular supply chain. For example,information regarding the supply chain of a food product may be ofinterest to regulators and/or consumers.

It may be beneficial to share information on a limited basis todemonstrate that a certain component is not involved, or otherwise traceitems and/or processes involved in the supply chain. It may be desirableto share information on a limited basis for studies that might benefitmultiple supply chain entities and/or the consumers, or to prove ordisprove some fact to regulators. Increased traceability can also limitthe potentially huge economic and safety consequences of counterfeitingand defective products. For example, food and/or brand name piracyconcerns can cost the industry billions of dollars each year, and cancause the industry to implement anti-counterfeit technologies to protectproducts, brand and/or market. Recall is also a critical service whereremedial activities are to be applied to a defective product orcomponent thereof, making it desirable to identify locations of affectedproduct. Increased traceability along a supply chain can increase trustand limit the consequences of events closer to their source in thesupply chain.

Enhanced supply chain robustness improves customer experience bydelivering products reliably and decreasing the costs and manual effortassociated with debugging and fixing errors in the delivery of productsand services. Supply chain participants are motivated to improverobustness but need improved mechanisms to efficiently manage thesharing of information. Collaborative information systems can includelarge amounts of dynamic data, such as concerning transactionalinformation of products and/or services of a supply chain. Applyingappropriate data retention policies to data sources that may begeographically and organizationally diverse, subject to multiple legalrequirements, and can be maintained over long periods of time asdata-related considerations change, can be challenging.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating a computing system according to anexample of the present disclosure.

FIG. 2A is a diagram illustrating an example computing platform forproviding collaborative information services according to an example ofthe present disclosure.

FIG. 2B is a diagram illustrating another example computing platform forproviding collaborative information services according to an example ofthe present disclosure.

FIG. 3 is a diagram illustrating components of the collaborativeinformation services platform according to an example of the presentdisclosure.

FIG. 4 is a diagram illustrating an authorization and attestationservice for a computing platform according to an example of the presentdisclosure.

FIG. 5 is a diagram illustrating a discovery service for a computingplatform according to an example of the present disclosure.

FIG. 6 is a diagram illustrating a cloud index cache arrangementaccording to an example of the present disclosure.

FIG. 7 is a diagram illustrating a serialized data service according toan example of the present disclosure.

FIG. 8 is a flow chart illustrating an example of a method forserialized data service according to an example of the presentdisclosure.

DETAILED DESCRIPTION

The present disclosure includes a system and method for a serializeddata service. An example method for a serialized data service [801]includes retrieving serialized data to a data service [803], andaugmenting the serialized data with information corresponding to one ormore data retention policies [809]. The augmented serialized data isstored to a data source [811]. The augmented serialized data is removedfrom the data source based on the augmented information [813].

The collaborative information system of the present disclosure isarranged generally in a hub-and-spokes configuration, with acollaborative information services (CIS) computing platform programmedwith query services as a hub, and participant data sources as thespokes. Participants in the collaborative information system make someportion of their respective data sources available to queries of otherparticipants. According to the present disclosure, participantsauthorize query services with constrained data inputs and known outputattributes. A query service is a group of one or more queries executedto ascertain information of interest. A query set is a number of queriesthat can be related to one another in some aspect. A query service mayinclude queries from one or more query sets, or the queries comprisingmultiple query services may all be included in a single query set. Thatis, a query service may be a subset of one or more query sets, ormultiple query services may be subsets of a single query set, dependingon the queries comprising the query set(s) and the query service(s).

According to the collaborative information system of the presentdisclosure, attributes of each query service are defined prior to thequery service being invoked by any participant. Each data sourcecontrolling entity must implement pre-defined queries of a query serviceto involve their respective data source. For example, the type of dataand scope of data sources associated with a particular query service ispre-defined, the attributes of a respective query service being madeavailable to participants so that they can determine whether, and towhat extent, to expose their respective data source to the queries of aquery service. That is, each query service is implemented using a“canned” group of queries that can be applied to a data source, ifauthorized by the control entity of the data source and the queriesimplemented on the respective data source. Similarly, scope, format,etc., of query results are also defined prior to a query service beinginvoked. Such a pre-defined result may be computed and mutuallyadvantageous for the query invoker and data providers to share. It mayobfuscate aspects of the data obtained by the embedded queries tocompute intermediate results but that the data providers may not want orneed to share directly. This may encourage providers to share more datawith the knowledge that those invoking query services only have accessto the possibly more limited computed results. Having pre-definedqueries in terms of inputs and outputs enables collaborative informationsystem participants to make informed decisions as to the type and extentof queries, and therefore query services, to which they are willing toallow their respective data source to be exposed.

According to the collaborative information system of the presentdisclosure, information needed for authorized results (e.g., raw datasource data, intermediate computations, etc.) may or may not bepresented to the participant that invokes a particular query service. Insome previous approaches, the data being made available by eachparticipant needed to be stored (e.g., duplicated to) a particulardedicated computing system storage media. However, the collaborativeinformation system of the present disclosure does not requireparticipant-contributed information to be maintained in a common,dedicated location. That is, the collaborative information system of thepresent disclosure enables participants to self-configure variousauthorization models that in turn control access of other participantsto their data source(s). In this manner, dispersed data sources,including cloud based data sources, can be controlled to the degreedesired by the data source control entity at their original location.

According to the collaborative information system of the presentdisclosure, authorization to access data of a data source is made withrespect to query services of the collaborative information servicescomputing platform, rather than peer-to-peer with each participant inthe collaborative information system. Thus, the collaborativeinformation system of the present disclosure enables self-configurationof authorizations by participants with fewer interventions by their ITstaff. Also, automated and repeated discovery of information availablefrom portions of the data sources available to the query servicessupports the efficient implementation of real time query services on alarge scale.

FIG. 1 is a diagram illustrating a computing system according to anexample of the present disclosure. The computing system shown in FIG. 1is a networked computing system, such as a cloud computing system 100.Cloud computing system 100 is one example implementation of a networkedcomputing system. However, examples of the present disclosure are notlimited to a particular computing system configuration. By “cloudcomputing” is meant Internet-based computing that can effectively sharephysical computing resources, including software and/or informationamong a number of users. Cloud computing enables fine-grainedprovisioning of computing resources in real time to achieve dynamicscalability in response to varying data processing levels.

Cloud computing system 100 can include a private cloud 110communicatively coupled to a public cloud 102. The public cloud 102 caninclude a number of computing resources networked together by variouscommunication channels 106, including first computing resources 104external to a hybrid cloud 112 (discussed further below), and secondcomputing resources external to the hybrid cloud 112. The computingresources 104 comprising the public cloud 102 can be of varying size andcapability, may be respectively geographically dispersed from oneanother or be commonly located, and may be respectively owned and/oroperated by any number of independent entities. The size, capabilities,and configuration of public cloud 102 can be dynamically changed asdictated by service level agreements, actual computing requirements, andfor other factors applicable to cloud computing arrangements.

The term “public” refers to computing resources offered and/or availablefor use by entities (e.g., the public) other than the computing resourceowners, usually in exchange for compensation (e.g., computing capabilityfor hire). Computing resources 104 comprising the public cloud 102 maybe owned by discrete entities, which may or may not be participants in aparticular collaborative information system for which the computingresources are being employed.

A respective private owner/operator can make owner/operator-maintainedcomputing resources available to the public for hire. The term “private”refers to computing resources dedicated for use by a limited group ofusers (e.g., one entity such as a company or other organization). Thatis, “private” is intended to mean reserved for use by some and notavailable to the public.

The private cloud 110 can be comprised of a number of computingresources 105. While a single server is shown in FIG. 1, the privatecloud can be comprised of multiple computing resources 105. A computingresource 105 can include control circuitry such as a processor, a statemachine, application specific integrated circuit (ASIC), controller,and/or similar machine. As used herein, the indefinite articles “a”and/or “an” can indicate one or more than one of the named object. Thus,for example, “a processor” can include one processor or more than oneprocessor, such as a parallel processing arrangement. The controlcircuitry can have a structure that provides a given functionality,and/or execute computer-readable instructions that are stored on anon-transitory computer-readable medium 107. The non-transitorycomputer-readable medium 107 can be integral, or communicativelycoupled, to a computing resource 105, in either in a wired or wirelessmanner. For example, the non-transitory computer-readable medium 107 canbe an internal memory, a portable memory, a portable disk, or a memorylocated internal to another computing resource (e.g., enabling thecomputer-readable instructions to be downloaded over the Internet). Thenon-transitory computer-readable medium can have computer-readableinstructions stored thereon that are executed by the control circuitry(e.g., processor) to provide a particular functionality.

The non-transitory computer-readable medium 107, as used herein, caninclude volatile and/or non-volatile memory. Volatile memory can includememory that depends upon power to store information, such as varioustypes of dynamic random access memory (DRAM), among others. Non-volatilememory can include memory that does not depend upon power to storeinformation. Examples of non-volatile memory can include solid statemedia such as flash memory, EEPROM, phase change random access memory(PCRAM), among others. The non-transitory computer-readable medium 107can include optical discs, digital video discs (DVD), high definitiondigital versatile discs (HD DVD), compact discs (CD), laser discs, andmagnetic media such as tape drives, floppy discs, and hard drives, solidstate media such as flash memory, EEPROM, phase change random accessmemory (PCRAM), as well as other types of machine-readable media.

A data source 115 owned by entity 114 (e.g., organization, naturalperson) can be part of private cloud 110, or as shown in FIG. 1,communicatively coupled to private cloud 110. That is, information underthe control of organization 114 may be stored in the computing resourcescomprising private cloud 110, or be stored in memory accessible byprivate cloud 110. The data source 115 may be used in a collaborativeinformation system, with organization 114 making some portion of theinformation stored in data source 115 available to other participants inthe collaborative information system, as is further described below.

Although not shown in FIG. 1 for clarity, private cloud 110 can alsoinclude a number of computing resources (e.g., physical resources,software, etc.), such as computing resources 104, networked together byvarious communication channels 106. The computing resources of privatecloud 110 can be homogeneous or of varying size and capability, may begeographically dispersed from one another or be commonly located, andmay be owned and/or operated by one or any number of independententities that dedicate some or all of their computing resources for theprivate use of one entity (e.g., organization 114). The size,capabilities, and configuration of the private cloud can change asdictated by service level agreements, dynamic computing requirements,and other factors applicable to cloud computing arrangements.

A portion 118 of cloud computing system 100 may be owned by organization114, and another portion 120 of cloud computing system 100 may be ownedby entities other than organization 114. As such, in addition to beingprivate, private cloud 110 may be referred to as an internal cloud aswell (e.g., a cloud computing arrangement internal to organization 114and dedicated to the private use of organization 114). Considerationsregarding specific cloud computing system configuration may includesecurity, logging, auditing/compliance, firewall boundary location,and/or company policy, among others. Organization 114 may maintainadditional computing resources not dedicated to the private use oforganization 114 (e.g., available for contract use by the public as partof a cloud).

A number of entities 116 may be users of the public cloud 102 (e.g., asa networked computing system). Some entities 116 may have data sources115 that may be used in (e.g., made available for query by participants)a collaborative information system, and other entities 116 using thepublic cloud may participate in the collaborative information system(e.g., invoke queries) but not have, or make available, a data source toother participants. There are many products from a variety of differentvendors that can implement data sources that may be used forcollaborative information services via standard interfaces for dataqueries.

While cloud computing system 100 is illustrated in FIG. 1 as twocommunicatively coupled clouds (e.g., private and public), examples ofthe present disclosure are not so limited, and the method of the presentdisclosure can be implemented using a private cloud 110, public cloud102, or a hybrid cloud 112 comprising some portion of the public cloud102 and the private cloud 110 made available for such use.

Not all of the components and/or communication channels illustrated inthe figures are required to practice the system and method of thepresent disclosure, and variations in the arrangement, type, andquantities of the components may be made without departing from thespirit or scope of the system and method of the present disclosure.Network components can include personal computers, laptop computers,mobile devices, cellular telephones, personal digital assistants, or thelike. Communication channels may be wired or wireless. Computing devicescomprising the computing system are capable of connecting to anothercomputing device to send and receive information, including web requestsfor information from a server. A server may include a server applicationthat is configured to manage various actions, for example, a web-serverapplication that is configured to enable an end-user to interact withthe server via the network computing system. A server can include one ormore processors, and non-transitory computer-readable media (e.g.,memory) storing instructions executable by the one or more processors.That is, the executable instructions can be stored in a fixed tangiblemedium communicatively coupled to the one or more processors. Memory caninclude RAM, ROM, and/or mass storage devices, such as a hard diskdrive, tape drive, optical drive, solid state drive, and/or floppy diskdrive.

The non-transitory computer-readable media can be programmed withinstructions such as an operating system for controlling the operationof server, and/or applications such as a web page server. Thecollaborative information services (CIS) platform and/or applications(e.g., services and/or models) may be implemented as one or moreexecutable instructions stored at one or more locations within volatileand/or non-volatile memory. Computing devices comprising the computingsystem implementing the collaborative information system may alsoinclude an internal or external database, or other archive medium forstoring, retrieving, organizing, and otherwise managing data sourcesand/or the functional logic of the collaborative information system.

Computing devices comprising the computing system may also be mobiledevices configured as client devices, and include a processor incommunication with a non-transitory memory, a power supply, one or morenetwork interfaces, an audio interface, a video interface, a display, akeyboard and/or keypad, and a receiver. Mobile devices may optionallycommunicate with a base station (not shown), or directly with anothernetwork component device. Network interfaces include circuitry forcoupling the mobile device to one or more networks, and is constructedfor use with one or more communication protocols and technologies.Applications on client devices may include computer executableinstructions stored in a non-transient medium which, when executed by aprocessor, provide such functions as a web browser to enable interactionwith other computing devices such as a server, and/or the like.

FIG. 2A is a diagram illustrating an example computing platform forproviding collaborative information services according to an example ofthe present disclosure. The systems and methods of the presentdisclosure for collaborative information services are illustratedthroughout this description with respect to a supply chain applicationof the collaborative information system. However, implementation of thecollaborative information system of the present disclosure is notlimited to supply chains, and other collaborative information serviceimplementations are contemplated, including SaaS implementations.

A networked computing system implementing collaborative informationservices (CISs) can be applied to the information associated with asupply chain to provide a secure and trusted registry for supplier andcustomer information. Such a collaborative information system can act asa cache for information that connects services, partners, and customers.For example, suppliers may register products they sell with thecollaborative information system, and customers may register productsthey use.

The collaborative information system can be used, for example, toprovide a recall service upon a product associated with the supplychain. Information in the collaborative information system can causerecall messages to be sent to specific recipients (e.g., existingcustomers), rather than be broadcast generally (e.g., sent to potentialcustomers as well). Recall messages can include detailed instructionsappropriate for a particular recall, or series of recalls. Such a recallservice could record the messages sent so that a supplier has theassurance that registered customers are notified.

A customer may also act as a supplier of a product that includes otherproducts as parts. If one of the parts is recalled, then the customermay issue an additional recall via the collaborative information systemfor the composite product. In this way recall messages can traverse anappropriate portion of the supply chain without being over-, or under-,inclusive.

FIG. 2A illustrates an example architecture of a collaborativeinformation system 222. For example, some, or all, of the participantsin the supply chain of interest can be participants 238 in thecollaborative information system 222. Collaborative information systemparticipants 238 may have zero or more data sources 240 (e.g.,databases, memory) that may be made available to the collaborativeinformation system 222, and other participants 238 therein. Such datasources 240 can be widely deployed, owned and/or controlled byindependent entities, and can be implemented with standard interfacesfor sharing supply chain information. Some participants 238 of thecollaborative information system 222 may not provide a data source tothe collaborative information system 222 (e.g., have zero data sources).Some participants 238 of the collaborative information system 222 mayparticipate by invoking query services without offering a data source.For example, regulators or consumers may be collaborative informationsystem participants 238 without also being data source providers.

The collaborative information system 222 illustrated in FIG. 2A includesa CIS platform 224 communicatively coupled to a plurality ofcollaborative information participants 238 interconnected via acommunication network 239, each participant 238 having a data source240. According to an example embodiment, the collaborative informationsystem 222 can be implemented by a networked computing system such asthe cloud computing system 100 illustrated in FIG. 1, with the CISplatform 224 being implemented as a cloud platform. That is, the CISplatform can be implemented using geographically diverse anddynamically-configured computing resources.

The CIS platform 224 is communicatively coupled to the data sources 240associated with participants in the collaborative information system viacommunication link 239. The CIS platform 224 is programmed with CISs 226(e.g., query services). Each query service 226 is implemented using oneor more queries (e.g., 227-1, 227-2, . . . 227-N) operable on authorizedportions of participant data sources 240. That is, each CIS can be a setof one or more queries involving the available data sources 240. A groupof queries may be the same or different (e.g., more or less inclusive)than a query set, which is discussed further below. In other words, eachquery service may be implemented using a standardized group (e.g.,“canned set”) of queries. The CIS platform 224 is further programmedwith indications from individual ones of the plurality of collaborativeinformation participants 238 authorizing some portion of their datasource 240 to be available to the one or more queries (e.g., 227-1,227-2, . . . 227-N) defined by at least one query service 226.Participants 238 can make all or part of their data source available toall or part of a respective query, or query set. A participant 238 mayrequire its IT staff to enable a query or query set. However, onceenabled, the participant may then authorize additional query servicesthat already have their required queries implemented without furtherinvolvement of the IT staff.

FIG. 2B is a diagram illustrating another example computing platform forproviding collaborative information services according to an example ofthe present disclosure. In addition to the query services 226, the CISplatform 224 can be programmed with a service modeling service 228, anauthorization configuration service 230, an authorization andattestation service 232, a cloud index service 234, and anauthentication service 236.

The service modeling service 228 describes the queries issued by eachquery service 226, as well as the attributes (e.g., format, scope) ofthe output results by a respective query service 226. The authorizationconfiguration service 230 is a portal that allows CIS participants tocontrol the access to their data sources by query services 226 and/orindividual queries. The authorization portion of the authorization andattestation service 232 ensures that just authorized queries byauthorized query services 226 access participant data sources 240. Theattestation portion of the authorization and attestation service 232logs interactions of the various services and the participant's datasources 240, if desired by a participant 238, to serve as an audittrail. The cloud index service 234 maintains a cache of authorizedinformation from data sources 240 that enable the efficientimplementation of query services which require information for just afraction of the potentially large number of data sources 240.

The CIS platform 224 is programmed (e.g., with executable instructionsstored in a memory and executable on a processor) to implement thefollowing functionality. Participants 238 in the collaborativeinformation system 222 authenticate with the CIS platform 224 (e.g.,peer-to-platform and platform-to-peer, together referred to aspeer-to-platform-to-peer) rather than directly with each other (e.g.,peer-to-peer). For example, a first participant 238 can authorize theCIS platform 224 to execute certain query services and/or queries oncertain portions of the first participant's data sources 240, providingthe query results in certain, specified ways (explained further below).The first participant 238 can further authorize the CIS platform 224 topermit certain other participants to invoke the authorized queryservices (and/or queries) on the authorized portions of the firstparticipant's data sources 240.

Thereafter, another participant 238, if authorized by the platform as aresult of the platform being authorized to permit the anotherparticipant 238, can cause the CIS platform 224 to invoke an authorizedquery service 226 (and/or queries). That is, the first participant canauthorize a query, a query set, and/or a CIS, to involve portions of thefirst participant's data sources specified by the first participantcorresponding to each query. Subsequently, one or more participant(s),if authorized with respect to the query, or query set and/or a queryservice, can then execute the query, a query set, and/or a queryservice, to involve portions of the first participant's data sourcesthat the first participant specified corresponding to a respectivequery. In this manner, the first participant does not have toindividually authorize (and monitor or control) each subsequentparticipant individually that wishes to execute the query, or query setand/or query service. Provisions are explained below for creating newqueries and/or query services (i.e., groups of queries).

The peer-to-platform and platform-to-peer authorization functionality ofthe CIS platform 224 enables participants 238 to authorize CIS servicesthat access data in standardized (e.g., known) ways instead of having tomanage point-to-point data sharing rules among participants that can betypical of previous information sharing approaches. The peer-to-platformand platform-to-peer authorization relationship structure, effectively ahub-and-spokes configuration, enables greater scalability from theperspective of managing the collaborative information systemarrangements. The peer-to-platform and platform-to-peer authorizationrelationship structure, and standardized querying with known queryservice result attributes, also enables greater data sharing whilegreatly reducing the risk of data mining by competitors.

FIG. 3 is a diagram illustrating components of the collaborativeinformation services platform according to an example of the presentdisclosure. A portal access system 342 includes a portal 344communicatively coupled to a number of models and services. The portal344 provides access to collaborative information system models thatenable greater self-configuration by participants of the CIS platform(e.g., FIG. 2A at 224). Models refer to logic that may be implemented inhardware or by executable instructions stored in a memory and executableby a processor to perform a function. Participants configure models viathe portal 344.

FIG. 3 shows portal 344 providing access to the service modeling service328 via communication link 347. The service modeling service iscommunicatively coupled to a service model 346. An authorized servicedeveloper can use the portal 344 to manage the lifecycle of a particularservice (e.g., a query service that relies on a set of one or morequeries). The portal can support both human and programmaticinteractions with the same level of functionality that includes theregistration, categorization, and description of the service. Thedescription of the service includes a description of the informationused by the service (e.g., the queries), and the output provided by theservice (e.g., the result attributes).

FIG. 3 shows portal 344 providing access to the service taxonomy model348 via communication link 349. Participants can use the portal 344 toindicate which services in the service taxonomy model 348 they arewilling to support for specific categories of data, and/or forparticular locations of their data sources. The service taxonomy model348 is communicatively coupled to the service modeling service 328 viacommunication link 363 such that they may exchange information. Servicescan be categorized to facilitate working with large numbers of services.For example, a participant may authorize a category of services insteadof having to authorize a quantity of services individually. In addition,services properly added to a prior-authorized category may be authorizedby virtue of the proper categorization to the authorized category.

Services can be categorized in hierarchies based on the service taxonomymodel 348 that can reflect one or more of: type of service, type ofresult(s), and/or query/queries sets being executed to implement theservice. Services can be related to other services, inherently orinvoked by a participant in a related fashion (e.g., applying a logicalfunction to the results of queries to arrive at a desired output). Forexample, a query service “A” may be implemented using queries that are asubset of a query service “B.” As such, query services “A” and “B” areinherently related, with query service “A” being a child of queryservice “B.” In another example, a participant may wish to interrogatedata sources to find an output data set reflecting query service “C” ANDquery service “D.” In this manner, the participant invokes queries “C”and “D” in a related fashion. In yet another example a second queryservice may be run in the results of a first query service, such as adownstream consumer service may be run on a service to create anupstream set of data which data providers are willing to share withconsumers.

The service taxonomy model 348 can be set up to be static rule based,and/or can include conditional taxonomies. For example, a data providermay be willing to share data for query service “C” run alone. The dataprovider may also be willing to share data for query service “D” runalone. However, the data provider may feel that the results of queryservice “C” AND query service “D” reveal too much information regardingthe relationship of certain data in the data provider's data source.Therefore, the service taxonomy model 348 can reflect that the resultsof query service “C” AND query service “D” are not available at all, orthat certain portions of the results are summarized to a higher levelthat is not so revealing, or obfuscated in some manner acceptable to thedata provider. Taxonomies concerning related services can also bereferred to as conditional taxonomies.

Queries themselves are described in the language(s) supported by datasources. Participants that are data source providers must enable supportfor such queries for a service to be able to run on their data source.Query sets are sets of queries that are often performed together, andcan be authorized subject to use of an appropriate conditional taxonomy.A service (e.g., a query service, discovery service, or other service)can be implemented (e.g., use) using one or more queries, one or morequery sets, or portions of one or more query sets. Several differentservices may have queries that belong to a particular query set. Where aparticipant authorizes a particular query set to involve portions of theparticipant's data sources, the participant may also authorize anyservice having queries derived entirely from the authorized particularquery set. By authorizing a number of query sets, a participant canchoose to authorize a wide range of services derived from the number ofquery sets implemented to operate on their data sources without havingto evaluate (and authorize) the services individually. According to someexamples of the present disclosure, a participant having a data source(e.g., data provider) can implement query sets with respect to theirdata source and use taxonomy model(s) to authorize services usingqueries of the implemented query sets. According to some examples, aparticipant may revoke or conditionally modify authorization of certainservices despite having authorized a query set that includes each of thequeries of the service. An authorization may be conditionally modifiedusing a conditional taxonomy. For example, the relationships betweenindividual services may be obfuscated for the presentation of data foran individual service. Therefore, a combination of two or more services(e.g., by logical operation) may not be possible without additionalconstraints even if the services are available individually. That is, a“composite” service may have different participation/access rightspursuant to a conditional taxonomy.

FIG. 3 shows portal 344 providing access to the query/query set model356 via communication link 357. Participants must implement the queriesand or query sets that are required for the services they choose toauthorize. Implementations for query sets for particular data sourceproducts can be made available for download to participants via theQuery/Query Set model 356. The query/query set model 356 iscommunicatively coupled to the service modeling service 328 viacommunication link 345, for example, to communicate to servicesauthorization of particular queries and/or query sets.

FIG. 3 shows portal 344 providing access to the data source model 354via communication link 355. Not all data sources will categorize dataaccording to the data taxonomy model 350. The data source model 354addresses this issue. If a participant's data source labels dataaccording to the taxonomy of the data taxonomy model 350, then queriesof a service are constrained based on the taxonomy of the data taxonomymodel 350. Otherwise, the query and/or results are further processed tocorrespond the participant's data source labels to the taxonomy (e.g.,according to a default mapping or list).

FIG. 3 shows portal 344 providing access to the participant taxonomymodel 352 via communication link 353. The participant taxonomy model 352defines groups of participants, such as end-consumers, growers,maintenance providers, etc. A participant may be part of zero or moregroups as defined in the participant taxonomy model 352. Groups ofparticipants can be used to further govern rights over who is permittedto invoke certain services that involve the participant's own data. Thatis, a participant may authorize a service to involve their data sourceexcept where the service is invoked by a specified other participant,group of participants, and/or or invoked along with (e.g., aggregatedwith) another service. For example, one service might provide productlocation information, and another service might provide product countinformation. A data provider may allow for other participants to runeither service individually, but disallow running the two services inaggregate with one another since doing so exposes too much information(e.g., a product count at each location). Or a participant may authorizea service to involve some portion of their data source where the serviceis invoked by one participant/group, and may authorize a service toinvolve some other (more or less or different) portion of their datasource where the service is invoked by another participant/group.

FIG. 3 shows portal 344 providing access to the data taxonomy model 350via communication link 351. The data taxonomy model 350 can beconfigured by a participant to further define a scope of access to theparticipant's data source with respect to certain categories of thedata, which may be further qualified by certain participants. That is, aparticipant may limit some (or all) portions of their data source for aparticular service. For example, a participant may limit a service toinvolve data from their data source that is publically reported, ratherthan not authorize the service at all. Or a participant my limit thescope of their data source to certain relevant kinds of data for aservice invoked by a specified participant, and/or subject to additionalconstraints with respect to combining (e.g., aggregating) services.

FIG. 3 shows portal 344 providing access to the authorization model 358via the synthesizer choices 359 and communication links 360 and 361. Aparticipant's configuration of one or more authorizations aresynthesized into the authorization model 358, which is used to governaccess to the participant's data sources. A participant's authorizationconfiguration specification can also be captured directly into theauthorization model 358. The authorization model 358 governs access tothe participant's data sources by limiting the access of respectivequery services by authorized other participants to specified portions ofthe participant's data sources.

A participant-configured authorization model makes it easier for aparticipant (e.g., any size organization) to support their ownparticipation in the collaborative information system than wasexperienced with previous (e.g., peer-to-peer) approaches where moreintervention may be needed from IT staff. An example of a service thatsupports self-configuration for participants and the platform is thediscovery service, which is discussed further with respect to FIG. 5.Like other services, the discovery service must be authorized by aparticipant. Once authorized for execution by the CIS platform, thediscovery service peruses the service models of the participant's otherauthorized services, recognizes the kinds of product category and/orproduct IDs that are considered in the queries, and then interacts witha participant's data sources to discover which products the participantsupports in its supply chain. This information is cached in a cloudindex to support the efficient operation of other authorized services.It guides the other authorized query services to participant datasources that are relevant for the query service. Without such adiscovery service, participants have to specifically registerinformation they choose to authorize. Thus, self-configuration canbenefit both the participant providing a data source, as well as theparticipant(s) that might wish to invoke services involving the datasource that can function more efficiently due to the previous discoveryprocess.

The service developer can describe a service, such as a query service,in the service model 346 using the service modeling service 328. Theservice developer can configure the service model 346 to indicate thequeries and/or query sets that are used by a query service, for example.Participants can access the service model 346 via the portal 344 tolearn the queries and/or query sets that are used by a particular queryservice.

FIG. 4 is a diagram illustrating an authorization and attestationservice for a computing platform according to an example of the presentdisclosure. Authorization logic 464 includes authorization andattestation service 466 having inputs from an authorization model 458and query services 446, and providing outputs to data sources 472 and aparticipant report repository 474. The function of the authorization andattestation service 466 is to ensure that the CIS platform (e.g.,services such as query services 446) perform authorized queries, forauthorized participants, involving authorized data sources, and does notperform unauthorized queries, queries involving unauthorized portions ofdata sources for a respective query, and/or queries invoked byunauthorized entities (including unauthorized participants).

In addition, another function of the authorization and attestationservice 466 is to maintain attestation logs 468 that can be used toaudit interactions between participants and the platform and/or datasources. The authorization and attestation service can log queriesand/or service invocations, among other activities that may be ofinterest, and can report results to participants and/or systemadministrators. According to one example embodiment, reports are storedin a participant report repository 474 via communication link 476.

The authorization and attestation service is guided by the authorizationmodels 458 as may be self-managed by each participant, including servicerelationship rules expressed in a conditional taxonomy, as previouslydiscussed. The authorization models 458 communicate with theauthorization and attestation service 466 via a communication link 478.The authorization and attestation service 466 can include a query shim470, a “shim” in the sense of being logic that fits between two otherlogic components so as to relate them (e.g., facilitate communication ofuseful information therebetween). The query shim 470 is programmed toensure that just authorized queries are made upon data sources 472(e.g., via communication link 480), and that just authorized results arereturned to the invokers of services. Authorized results may not includeraw data from the data sources, or intermediate results (e.g., resultscomputed from the raw data) in response to invoking a service.Authorized results returned to a participant may format, organize,and/or summarize query raw data and/or intermediate results intohigher-level authorized results that aggregate the raw data and/orintermediate results in order to maintain confidentiality of individualraw data, according to the service description. In this way, the rawdata from a data source and computed intermediate results are notexposed to an invoker of a service unless they are included in thedefinition of results for a particular service. Thus, a data sourceprovider is always aware of what data will be returned to an invoker ofa service and can use the knowledge to direct its own authorizationchoices.

FIG. 5 is a diagram illustrating a discovery service for a computingplatform according to an example of the present disclosure. Discoverylogic 582 includes the discovery service 584 communicatively coupled tothe authorization model 558 via communication link 583, andcommunicatively coupled to the authorization and attestation service 566via communication link 588, and communicatively coupled to an indexservice 586 (e.g., a cloud index service) via communication link 587.The discovery service 584 inspects the authorization model 558 to findwhat services are authorized by a participant. The services authorizedby a participant are determined from the authorization and attestationservice 566.

The discovery service 584 also inspects the queries of services andbuilds information regarding the kinds of master and transactional datathat may be accessed from a participant's data sources 572. According tosome examples of the present disclosure, master data can concern groupsof items (e.g., classifications), whereas transaction data can concernindividual items. For example with respect to a collaborativeinformation service applied in regards to a supply chain, master datamight concern attributes corresponding to various kinds of stereoequipment, but the discovery service might also discover transactionaldata such as the actual instances of stereo equipment in the datasources and activities (e.g., sale, fabrication steps, locations, dataof manufacture, component types/sources, etc.) involving the actualinstances of stereo equipment.

The discovery service 584 can then run queries to the participant's datasources 572, if authorized by respective participants, to find out whatkinds of corresponding master and transactional data are actuallypresent. The information that results from the discovery service 584 iscached in a collaborative information system index (e.g., a cloud index)586, which can be subsequently used to support the more efficient (e.g.,optimized) execution of query services. For example with respect to acollaborative information service applied in regards to a supply chain,a query service is invoked by a participant to operate on a particularbrand of stereo components across a number of data sources. However,since the services are defined before they are invoked by a participant,the discovery service 584 may have previously run the queries comprisingthe service being invoked and cached the results in the cloud index 586.Then, in response to the service being invoked by a participant causingthe queries, the cache can be used to quickly find which supply chainparticipants have such components, rather than having to query a largequantity of possible data sources in real time.

While a single cloud index is indicated in FIG. 5 for clarity, examplesof the present disclosure are not so limited. That is, the collaborativeinformation system of the present disclosure can include more than onecloud index, and/or cloud index caching arrangement (e.g., a cloud indexand associated interfaces and supporting data processing hardware and/orprogrammed functionality, as is further discussed with respect to FIG. 6below).

FIG. 6 is a diagram illustrating a cloud index cache arrangementaccording to an example of the present disclosure. The cloud index cachearrangement 690 includes a cloud index 692 communicatively coupled toeach of a registration interface 694, a data discovery interface 696, amaintenance interface 698, and a query engine 699. The cloud index cachearrangement 690 supports the collaborative information services. Asdiscussed above, the data discovery service (e.g., FIG. 5 at 584)populates the cloud index 692 with discovered information that can beused to optimize the execution of query services, for example, via adata discovery interface 696. The registration interface 694 andmaintenance interface 698 may be standardized interfaces for configuringand managing the cloud index 692 respectively. The query engine 699 canbe used to execute queries to populate and/or update the cloud index asmay be directed by the data discovery service (e.g., FIG. 5 at 584).

A query shim (e.g., FIG. 4 at 470) can also interact with the cloudindex 692 to obtain a list of data sources that may have data ofinterest to a query. The query shim ensures that only those data sourcesthat have authorized the queries for the particular instance of a queryservice are able to provide data for the query service. Similarly, thequery shim may interact with a number of cloud indexes as supported bydifferent instances of the collaborative information services platform.

FIG. 7 is a diagram illustrating a serialized data service according toan example of the present disclosure. Data sources can include manytypes and classifications of data. One such data classification ismaster data and transactional (e.g., serialized) data. For example,participants in a collaborative information system applied with respectto a supply chain can have master data that describes attributes of theitems which are the subject matter of the supply chain. Master data canbe higher level information, describing groups. More specifically withrespect to a supply chain example, master data may describe classes ofproducts, types of products, product attributes, locations of interestwith respect to the supply chain, and other information of the type thatmay be applicable to more than one supply chain item or activity. Thevolume of master data typically does not change with supply chainactivity. However, there can be limited exceptions to the generalcondition that the volume of master data does not change with supplychain activity. If a new product type is designed or manufactured forthe first time, new master data may be generated corresponding to thenew product. However, the master data corresponding to the new productcan remain static as additional quantities of the new product aremanufactured. Master data may on rare instances need to be modified foran existing product. One example is if a product has been so successfulthat serialized product information is no longer derivable from themaster. Another example is if product has been recalled such that only aportion of the master data is now relevant.

In contrast, the volume of transactional data typically does change(e.g., increase) with supply chain activity. For example, as aparticular product is manufactured, data may be captured to recordattributes specific to that particular product, such as date/time ofmanufacture, serial number, lot number, component inputs used in theproduct, present location, inventory quantity, etc. Transactionalinformation can be generated over time. As such, new transactionalinformation can be received to a data source over time in a serializedordering. As such, time-based transactional data can also be referred toas serialized data. Serialized data captures information about eventsthat happen as a supply chain operates. For example, the shipment of aproduct from one location to another is an event that occurs relative toa point in time and can have some corresponding serialized data. Thevolume of serialized data typically grows with supply chain activity.Again, there may be exceptions to the general condition that the volumeof transactional data changes (e.g., increases) with supply chainactivity, for example, where existing data is changed to reflect changesoccurring in the supply chain, rather than creating new data, may notincrease the volume of data. Transactional data may not be updated whenthe master data is updated. For example, in the case of recall within asupply chain, master data concerning a class of objects may need tochange while the transactional data concerning each particular objectremains the same.

Some collaborative information system participants may wish to havetheir serialized data hosted by a service. The advantages of such aserialized data hosting arrangement for the participants include nothaving to manage the increasing volumes of data, not having to maintaina highly available data source to provide information to thecollaborative information system, and not having to manage one or moredata retention policies that may be applicable to the serialized data.As used herein, a data retention policy refers to rules, other thanthose related to a measure of quality of a particular data item (e.g.,checksum, parity, etc.) by which a determination can be made to retain(or not) data within a non-transitory medium. For example, data that isnot stored in a storage medium due to a data quality and/or dataintegrity problem is not typically an application of a data retentionpolicy. However, data that is stored for a certain period of time andthen removed (e.g., can no longer be accessed or retrieved such as bythe change of an index to the data even where a memory actually remainsprogrammed with a data item) according to a predefined date-relatedcriteria can be an application of a data retention policy. According tosome examples, the data source of the host serialized data service maycontain data on behalf of multiple collaborative information systemparticipants.

FIG. 7 illustrates one example implementation of a serialized dataservice arrangement 781. A serialized data service 783 can receive datafrom a data source 772 via communication link 775. The data source 772may be that of a collaborative information system participant, which maybe an entity that is part of a supply chain, and the serialized dataservice 783 may be that of a host entity. The data source 772 may or maynot be a persistent store of data, or may be of sufficient volume tostore serialized data for some finite period of time.

Data can then be communicated to a serialized-data data source 789 viacommunication link 797, and stored therein. The serialized-data datasource 789 may be used as a data source for a collaborative informationsystem on behalf of the participant. That is, the serialized-data datasource 789 may be communicatively coupled to the computing platformprogrammed with the collaborative information services as shown at 240in FIGS. 2A and 2B, and similarly utilized. As with other data sources,such as those directly provided by a participant and as described above,access to data within the serialized-data data source 789 by otherparticipants in the collaborative information system is governed by theparticipant's authorization model (e.g., FIG. 3 at 358).

The serialized data in the serialized-data data source 789 may besubject to and governed by one or more retention policies. Retentionpolicies may be implemented by retention policy data taxonomy model 791.A retention policy data taxonomy model 791 is communicatively coupled tothe serialized-data data source 789 by communication link 793, such thatthe retention policy logic 791 may operate on the data stored in theserialized-data data source 789. For example, retention policy datataxonomy model 791 may specify to delete a certain portion of datastored in the serialized-data data source 789 after a particular datereflective of a data retention policy applicable to the certain portionof data.

The retention policy data taxonomy model 791 may be configured by theparticipant whose data is stored in the serialized-data data source 789(e.g., the data provider), for example, to implement applicableretention policies. Alternatively and/or in addition, the retentionpolicy data taxonomy model 791 may be configured by a third party onbehalf of the participant whose data is stored in the serialized-datadata source 789, such as by the host of the serialized data service 783,to implement applicable retention policies.

According to some example implementations of the serialized data servicearrangement 781, the serialized data service 783 may pull data from aparticipant's data source(s) 772, for example via communication link775. The serialized data service 783 can operate as other servicessupported by the collaborative information system computing platform,and can therefore be governed by a participant's authorization model(e.g., FIG. 3 at 358).

According to some example implementations of the serialized data servicearrangement 781, if a participant wants to push data from theparticipant's data source(s) 772 to the serialized data service 783, thedata can first be pushed to a proxy data storage medium 785 via acommunication link 771. The proxy data storage medium 785 receives andtemporarily caches the pushed data until it is pulled by the serializeddata service 783 via communication link 773.

A participant, and/or an authorized third party (e.g., a host) can setone or more retention policies for applicable portions of serializeddata by configuring the retention policy data taxonomy model 791. Theone or more retention policies can be enforced by the serialized dataservice 783 (e.g., as communicated over communication link 795) and/orthe serialized-data data source 789 (e.g., as communicated overcommunication link 793).

According to a more specific example of implementing a retention policy,the serialized data service 783 can augment a particular serialized dataitem with one or more appropriate tags that reflect the one or moreretention policies that govern(s) the particular data item (e.g., itemof data stored in a data source such as a database). The relationbetween a data item and one or more retention policies can be defined ina retention policy data taxonomy model 791 that is managed as part ofthe serialized data service 783, for example. A data provider 738 (i.e.,a participant having a data source) can configure a data source viacommunication link 762, and can configure the retention policy datataxonomy model 791 via communication link 765. The data item taggingprocess may be subject matter (e.g., supply chain), time/date, and/orlocation specific as specified in the retention policy data taxonomymodel 791.

Some retention policies may dictate that affected data be retained for aspecified period of time (e.g., two years), and then deleted thereafter.Other retention policies may be associated with specific subject matter(e.g., a particular supply chain) and further based on location (e.g., alocation where the data was captured and/or the location where a productwas finally sold. Other retention policies may be based on one or moreregulatory requirements, which can be complex (e.g., for a globallydistributed supply chain) associated with location of database items,border-crossing activities, and/or item ownership nationality, amongother considerations. Some retention policies can also be logicalcombinations of other retention polices, or be made to includeconditional criteria.

Conflicts in a retention policy applicable to a particular data item(e.g., of a data source) that can be recognized at the time of policyconfiguration can be brought to the attention of the data provider 738(e.g., via communication link 765). Recommendations for resolving theconflict may be given (e.g., a suggested ordering for the policy rulesto be implemented such as superseding rights for a given policy incomparison to another). Conflicts that are recognized at the time ofpolicy implementation can similarly be brought to the attention of thedata provider, possibly with recommendations for resolving the conflict.One solution for resolving retention policy conflicts is for the dataprovider to specify a final ordering for the implementation of theconflicting retention policy rules.

Retention policy rule conflicts can be resolved in other ways too.Retention policies can be mapped onto a same generalized graph or tree,and the policy recommendations at each tree compared in order to detectconflicts. Several retention policy conflict resolution methodologiesare possible, including: (1) one retention policy overrides another(e.g., always); (2) a superset retention policy invoking conflictingretention policies in a most restrictive combination is provided; (3)neither conflicting retention policy applies and the applied retentionpolicy defaults to a “safe” retention policy where the retention policyconflict cannot be resolved; and/or (4) full restriction until a manualfix provided. The above-mention retention policy conflict approaches arenon-exhaustive, and other possible actions are contemplated within thescope of the present disclosure.

The collaborative information services computing platform can beprogrammed to track and implement such requirements on behalf of itsmany participants (e.g., with respect to a supply chain, industry, etc.)rather than each participant having to independently do so for each datasource or group of data sources. Thus, the capability for centralizedimplementation of retention policies and/or uniform application acrossnumerous data sources can help to increase the ability of organizationsof all sizes to participate in collaborative information systems byreducing the associated burden of managing data in data sources.

The serialized data service 783 can make it easier for collaborativeinformation system participants to have their data hosted, to have theirdata contribute to the results collaborative information services, andto ensure that their data adheres to appropriate retention policies.Many data providers, that are collaborative information systemparticipants, especially those from smaller organizations, may benefitgreatly from outsourcing the hosting of their serialized data. Thisfrees a participant from the costs (including time) of hosting andmanaging a highly available data source.

A data provider that has its data reliably available to a collaborativeinformation system may be able to participate in strategies togetherwith other participants that reduce costs and/or energy usage, amongothers. Participants can take advantage of the availability of dataretention policies as supported by the collaborative information system.Participants can benefit from others having implemented a requiredpolicy rather than having to individually implement it. Certainretention policies can be configured to adhere to regulations asrequired by local laws simplifying participation in global trade.

The serialized data service arrangement 781 illustrated in FIG. 7 iscompatible with the collaborative information services computingplatform (e.g., FIG. 2B at 224). That is, the serialized-data datasource 789 can be utilized similar to data source 240 illustrated inFIG. 2B. The serialized data service 783 can be configured and managedin a manner described for other services with which the computingplatform is programmed. For example, serialized data service 783 can bemanaged such that only authorized data is stored therein, according tothe same authorization model (FIG. 3 at 358). As described previouslyfor data sources in general, the authorization model can also beconfigured to define how serialized data service 783 data may be used byother collaborative information services.

FIG. 8 is a flow chart illustrating an example of a method forserialized data service 801 according to an example of the presentdisclosure. The method 801 includes retrieving serialized data to aserialized data service 803. The method further includes augmenting theserialized data with information corresponding to one or more dataretention policies 809. The augmented serialized data is stored to adata source 811. The method also includes removing the augmentedserialized data from the data source based on the augmented information813.

Machine readable and executable instructions and/or logic, which areoperable to perform the method described in connection with FIG. 8, canbe present in whole or in part in the examples of other figures.Embodiments, however, are not limited to the particular examples givenherein.

Applying a common authorization model to data sources, including theserialized data service 783 and/or serialized-data data source 789reduces the likelihood of inconsistencies when managing authorizations.Prior approaches do not appear to exploit a single multi-dimensionalauthorization model to guide the storage of data in a data source,control data access to data provider authorized activities, or supportimplementation of subject matter aware (e.g., associated with a supplychain) and/or location aware retention policies for data that isavailable to the collaborative information system. Similar operabilityof data sources and services across the collaborative information systemcan reduce the challenges for a participant associated withparticipating in the collaborative information system.

The above specification, examples and data provide a description of themethod and applications, and use of the system and method of the presentdisclosure. Since many examples can be made without departing from thespirit and scope of the system and method of the present disclosure,this specification merely sets forth some of the many possibleembodiment configurations and implementations.

Although specific examples have been illustrated and described herein,those of ordinary skill in the art will appreciate that an arrangementcalculated to achieve the same results can be substituted for thespecific examples shown. This disclosure is intended to coveradaptations or variations of one or more examples of the presentdisclosure. It is to be understood that the above description has beenmade in an illustrative fashion, and not a restrictive one. Combinationof the above examples, and other examples not specifically describedherein will be apparent to those of skill in the art upon reviewing theabove description. The scope of the one or more examples of the presentdisclosure includes other applications in which the above structures andmethods are used. Therefore, the scope of one or more examples of thepresent disclosure should be determined with reference to the appendedclaims, along with the full range of equivalents to which such claimsare entitled.

Various examples of the system and method for collaborative informationservices have been described in detail with reference to the drawings,where like reference numerals represent like parts and assembliesthroughout the several views. Reference to various examples does notlimit the scope of the system and method for displaying advertisements,which is limited just by the scope of the claims attached hereto.Additionally, any examples set forth in this specification are notintended to be limiting and merely set forth some of the many possibleexamples for the claimed system and method for collaborative informationservices.

Throughout the specification and claims, the meanings identified belowdo not necessarily limit the terms, but merely provide illustrativeexamples for the terms. The meaning of “a,” “an,” and “the” includesplural reference, and the meaning of “in” includes “in” and “on.” Thephrase “in an embodiment,” as used herein does not necessarily refer tothe same embodiment, although it may.

In the foregoing Detailed Description, some features are groupedtogether in a single embodiment for the purpose of streamlining thedisclosure. This method of disclosure is not to be interpreted asreflecting an intention that the disclosed examples of the presentdisclosure have to use more features than are expressly recited in eachclaim. Rather, as the following claims reflect, inventive subject matterlies in less than all features of a single disclosed embodiment. Thus,the following claims are hereby incorporated into the DetailedDescription, with each claim standing on its own as a separateembodiment.

What is claimed:
 1. A method for a serialized data service [801],comprising: retrieving serialized data to a data service [803];augmenting the serialized data with information corresponding to one ormore data retention policies [809]; storing the augmented serializeddata to a data source [811]; and removing the augmented serialized datafrom the data source based on the augmented information [813].
 2. Themethod of claim 1, wherein retrieving serialized data to the serializeddata service [783] includes retrieving the serialized data from a datasource [772] of a data provider [738].
 3. The method of claim 1, furthercomprising pushing the serialized data from a data source [772] of adata provider [738] to a proxy data storage medium [785], whereinretrieving serialized data to the data service [783] includes retrievingthe serialized data from the proxy data storage medium [785].
 4. Themethod of claim 1, wherein the data source [789] is available to a queryservice [226] invoked by a participant [238] in a collaborativeinformation system [222].
 5. The method of claim 4, further comprisinginvoking the data service [783] through the collaborative informationsystem [222], wherein retrieving serialized data includes obtaining theserialized data as results of a query [227-1, 227-2, . . . , 227-N] ofthe data service [783].
 6. The method of claim 4, further comprisingconfiguring, by the data provider [738], an authorization model [358] tospecify attributes of authorized services involving the data source[789], including query services and the data service [783].
 7. Themethod of claim 4, further comprising configuring, by the data provider[738], a retention policy data taxonomy model [791] to specify acorrespondence between the one or more data retention policies and theaugmented information.
 8. The method of claim 4, further comprisingconfiguring, by a party other than the data provider, a retention policydata taxonomy model [791] to specify a correspondence between the one ormore data retention policies and the augmented information.
 9. Themethod of claim 1, wherein the one or more data retention policies arebased on an age of the serialized data.
 10. The method of claim 1,wherein the one or more data retention policies are based on a locationof where the serialized data was captured.
 11. The method of claim 1,further comprising resolving a conflict between the one or more dataretention policies, wherein resolving includes an action selected fromthe group comprising: (1) always overriding a particular one of the oneor more data retention policies in favor of another one of the one ormore data retention policies; (2) providing a superset data retentionpolicy invoking a most restrictive combination of the one or more dataretention policies; (3) providing a default safe data retention policyin lieu of the one or more data retention policies; and (4) fullyrestricting the serialized data until a manual fix can be provided. 12.A non-transitory computer-readable medium [107] having computer-readableinstructions stored thereon that, if executed by one or more processors,cause the one or more processors to: retrieve serialized data to aserialized data service [803]; augment the serialized data withinformation corresponding to one or more data retention policies [809]to which the serialized data is subject; and enforce the one or moredata retention policies upon the serialized data based on the augmentedinformation.
 13. The non-transitory computer-readable medium [107] ofclaim 12, wherein the computer-readable instructions to retrieveserialized data to a serialized data service [783] includescomputer-readable instructions to retrieve the serialized data from adata source [772] of a data provider [138].
 14. The non-transitorycomputer-readable medium [107] of claim 12, wherein thecomputer-readable instructions to retrieve serialized data to aserialized data service [783] includes computer-readable instructions toretrieve the serialized data from the proxy data storage medium [785].15. A computing system [100], comprising: a plurality of collaborativeinformation participants [238] interconnected via a communicationnetwork, each participant having zero or more data sources [240, 772]; acomputing platform [224] programmed with a number of services includinga query service [226] and a serialized data service [783], the queryservice [226] using one or more queries [227-1, 227-2, . . . ,227-N]operable on authorized portions of participant data sources [240,772]; wherein the serialized data service [783] is operable to: retrieveserialized data from a data source of at least one participant [803];augment the serialized data with information corresponding to one ormore data retention policies [809]; and enforce the one or more dataretention policies upon the serialized data based on the augmentedinformation.